Water systems such as rivers, lakes, and ponds can be highly dynamic systems where the volume may change in a time frame that can be from minutes to years. Changes in the water volume also have a strong influence on the system's physical parameters that change both over space and time. In the case of external disturbances such as rain, storms or drought, the physical parameters of water can change by orders of magnitude compared with values measured under normal conditions. These perturbations can result in a change in the physical parameter of the water system, such as turbidity and dissolved oxygen, and they can also pose stress on the living organism in the water system.
Existing practices in water monitoring are based on the acquisition of water samples once or twice per day that are analyzed in a laboratory with analysis results being available within days or weeks. While these laboratory analysis methods are accurate and well established, the obtained results with regard to composition and quality of the monitored water system only give a snapshot of the water system at the time the measurements were taken, i.e., days or weeks in the past.
Furthermore, the total number of sampling points of the water system is scarce due to the use of manual acquisition of the samples. This makes the correlation of quality and composition of acquisition points difficult due to reduced sampling points.
Simulations/modeling of the water system is possible, however, the lack of real time data makes the outcome difficult to verify.